Menambahkan kumpulan data yang tertunda

Gunakan penulis streaming JSON untuk menambahkan data yang tertunda.

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Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:

Contoh kode

Java

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di Panduan memulai BigQuery menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat Dokumentasi referensi BigQuery Java API.

Untuk melakukan autentikasi ke BigQuery, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk library klien.

import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BatchCommitWriteStreamsRequest;
import com.google.cloud.bigquery.storage.v1.BatchCommitWriteStreamsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.CreateWriteStreamRequest;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.FinalizeWriteStreamResponse;
import com.google.cloud.bigquery.storage.v1.JsonStreamWriter;
import com.google.cloud.bigquery.storage.v1.StorageError;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.cloud.bigquery.storage.v1.WriteStream;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Phaser;
import javax.annotation.concurrent.GuardedBy;
import org.json.JSONArray;
import org.json.JSONObject;
import org.threeten.bp.Duration;

public class WritePendingStream {

  public static void runWritePendingStream()
      throws DescriptorValidationException, InterruptedException, IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "MY_PROJECT_ID";
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";

    writePendingStream(projectId, datasetName, tableName);
  }

  public static void writePendingStream(String projectId, String datasetName, String tableName)
      throws DescriptorValidationException, InterruptedException, IOException {
    BigQueryWriteClient client = BigQueryWriteClient.create();
    TableName parentTable = TableName.of(projectId, datasetName, tableName);

    DataWriter writer = new DataWriter();
    // One time initialization.
    writer.initialize(parentTable, client);

    try {
      // Write two batches of fake data to the stream, each with 10 JSON records.  Data may be
      // batched up to the maximum request size:
      // https://cloud.google.com/bigquery/quotas#write-api-limits
      long offset = 0;
      for (int i = 0; i < 2; i++) {
        // Create a JSON object that is compatible with the table schema.
        JSONArray jsonArr = new JSONArray();
        for (int j = 0; j < 10; j++) {
          JSONObject record = new JSONObject();
          record.put("col1", String.format("batch-record %03d-%03d", i, j));
          jsonArr.put(record);
        }
        writer.append(jsonArr, offset);
        offset += jsonArr.length();
      }
    } catch (ExecutionException e) {
      // If the wrapped exception is a StatusRuntimeException, check the state of the operation.
      // If the state is INTERNAL, CANCELLED, or ABORTED, you can retry. For more information, see:
      // https://grpc.github.io/grpc-java/javadoc/io/grpc/StatusRuntimeException.html
      System.out.println("Failed to append records. \n" + e);
    }

    // Final cleanup for the stream.
    writer.cleanup(client);
    System.out.println("Appended records successfully.");

    // Once all streams are done, if all writes were successful, commit all of them in one request.
    // This example only has the one stream. If any streams failed, their workload may be
    // retried on a new stream, and then only the successful stream should be included in the
    // commit.
    BatchCommitWriteStreamsRequest commitRequest =
        BatchCommitWriteStreamsRequest.newBuilder()
            .setParent(parentTable.toString())
            .addWriteStreams(writer.getStreamName())
            .build();
    BatchCommitWriteStreamsResponse commitResponse = client.batchCommitWriteStreams(commitRequest);
    // If the response does not have a commit time, it means the commit operation failed.
    if (commitResponse.hasCommitTime() == false) {
      for (StorageError err : commitResponse.getStreamErrorsList()) {
        System.out.println(err.getErrorMessage());
      }
      throw new RuntimeException("Error committing the streams");
    }
    System.out.println("Appended and committed records successfully.");
  }

  // A simple wrapper object showing how the stateful stream writer should be used.
  private static class DataWriter {

    private JsonStreamWriter streamWriter;
    // Track the number of in-flight requests to wait for all responses before shutting down.
    private final Phaser inflightRequestCount = new Phaser(1);

    private final Object lock = new Object();

    @GuardedBy("lock")
    private RuntimeException error = null;

    void initialize(TableName parentTable, BigQueryWriteClient client)
        throws IOException, DescriptorValidationException, InterruptedException {
      // Initialize a write stream for the specified table.
      // For more information on WriteStream.Type, see:
      // https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/WriteStream.Type.html
      WriteStream stream = WriteStream.newBuilder().setType(WriteStream.Type.PENDING).build();

      // Configure in-stream automatic retry settings.
      // Error codes that are immediately retried:
      // * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
      // Error codes that are retried with exponential backoff:
      // * RESOURCE_EXHAUSTED
      RetrySettings retrySettings =
          RetrySettings.newBuilder()
              .setInitialRetryDelay(Duration.ofMillis(500))
              .setRetryDelayMultiplier(1.1)
              .setMaxAttempts(5)
              .setMaxRetryDelay(Duration.ofMinutes(1))
              .build();

      CreateWriteStreamRequest createWriteStreamRequest =
          CreateWriteStreamRequest.newBuilder()
              .setParent(parentTable.toString())
              .setWriteStream(stream)
              .build();
      WriteStream writeStream = client.createWriteStream(createWriteStreamRequest);

      // Use the JSON stream writer to send records in JSON format.
      // For more information about JsonStreamWriter, see:
      // https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1beta2/JsonStreamWriter.html
      streamWriter =
          JsonStreamWriter.newBuilder(writeStream.getName(), writeStream.getTableSchema())
              .setRetrySettings(retrySettings)
              .build();
    }

    public void append(JSONArray data, long offset)
        throws DescriptorValidationException, IOException, ExecutionException {
      synchronized (this.lock) {
        // If earlier appends have failed, we need to reset before continuing.
        if (this.error != null) {
          throw this.error;
        }
      }
      // Append asynchronously for increased throughput.
      ApiFuture<AppendRowsResponse> future = streamWriter.append(data, offset);
      ApiFutures.addCallback(
          future, new AppendCompleteCallback(this), MoreExecutors.directExecutor());
      // Increase the count of in-flight requests.
      inflightRequestCount.register();
    }

    public void cleanup(BigQueryWriteClient client) {
      // Wait for all in-flight requests to complete.
      inflightRequestCount.arriveAndAwaitAdvance();

      // Close the connection to the server.
      streamWriter.close();

      // Verify that no error occurred in the stream.
      synchronized (this.lock) {
        if (this.error != null) {
          throw this.error;
        }
      }

      // Finalize the stream.
      FinalizeWriteStreamResponse finalizeResponse =
          client.finalizeWriteStream(streamWriter.getStreamName());
      System.out.println("Rows written: " + finalizeResponse.getRowCount());
    }

    public String getStreamName() {
      return streamWriter.getStreamName();
    }

    static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {

      private final DataWriter parent;

      public AppendCompleteCallback(DataWriter parent) {
        this.parent = parent;
      }

      public void onSuccess(AppendRowsResponse response) {
        System.out.format("Append %d success\n", response.getAppendResult().getOffset().getValue());
        done();
      }

      public void onFailure(Throwable throwable) {
        synchronized (this.parent.lock) {
          if (this.parent.error == null) {
            StorageException storageException = Exceptions.toStorageException(throwable);
            this.parent.error =
                (storageException != null) ? storageException : new RuntimeException(throwable);
          }
        }
        System.out.format("Error: %s\n", throwable.toString());
        done();
      }

      private void done() {
        // Reduce the count of in-flight requests.
        this.parent.inflightRequestCount.arriveAndDeregister();
      }
    }
  }
}

Node.js

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Node.js di Panduan memulai BigQuery menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat Dokumentasi referensi BigQuery Node.js API.

Untuk melakukan autentikasi ke BigQuery, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk library klien.

const {adapt, managedwriter} = require('@google-cloud/bigquery-storage');
const {WriterClient, JSONWriter} = managedwriter;
const {BigQuery} = require('@google-cloud/bigquery');

async function appendRowsPendingStream() {
  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // projectId = 'my_project';
  // datasetId = 'my_dataset';
  // tableId = 'my_table';

  const destinationTable = `projects/${projectId}/datasets/${datasetId}/tables/${tableId}`;
  const streamType = managedwriter.PendingStream;
  const writeClient = new WriterClient({projectId: projectId});
  const bigquery = new BigQuery({projectId: projectId});

  try {
    const dataset = bigquery.dataset(datasetId);
    const table = await dataset.table(tableId);
    const [metadata] = await table.getMetadata();
    const {schema} = metadata;
    const storageSchema =
      adapt.convertBigQuerySchemaToStorageTableSchema(schema);
    const protoDescriptor = adapt.convertStorageSchemaToProto2Descriptor(
      storageSchema,
      'root'
    );

    const connection = await writeClient.createStreamConnection({
      streamType,
      destinationTable,
    });

    const streamId = connection.getStreamId();
    console.log(`Stream created: ${streamId}`);

    const writer = new JSONWriter({
      connection,
      protoDescriptor,
    });

    let rows = [];
    const pendingWrites = [];

    // Row 1
    let row = {
      row_num: 1,
      bool_col: true,
      bytes_col: Buffer.from('hello world'),
      float64_col: parseFloat('+123.44999694824219'),
      int64_col: 123,
      string_col: 'omg',
    };
    rows.push(row);

    // Row 2
    row = {
      row_num: 2,
      bool_col: false,
    };
    rows.push(row);

    // Row 3
    row = {
      row_num: 3,
      bytes_col: Buffer.from('later, gator'),
    };
    rows.push(row);

    // Row 4
    row = {
      row_num: 4,
      float64_col: 987.6539916992188,
    };
    rows.push(row);

    // Row 5
    row = {
      row_num: 5,
      int64_col: 321,
    };
    rows.push(row);

    // Row 6
    row = {
      row_num: 6,
      string_col: 'octavia',
    };
    rows.push(row);

    // Set an offset to allow resuming this stream if the connection breaks.
    // Keep track of which requests the server has acknowledged and resume the
    // stream at the first non-acknowledged message. If the server has already
    // processed a message with that offset, it will return an ALREADY_EXISTS
    // error, which can be safely ignored.

    // The first request must always have an offset of 0.
    let offsetValue = 0;

    // Send batch.
    let pw = writer.appendRows(rows, offsetValue);
    pendingWrites.push(pw);

    // Reset rows.
    rows = [];

    // Row 7
    row = {
      row_num: 7,
      date_col: new Date('2019-02-07'),
    };
    rows.push(row);

    // Row 8
    row = {
      row_num: 8,
      datetime_col: new Date('2019-02-17T11:24:00.000Z'),
    };
    rows.push(row);

    // Row 9
    row = {
      row_num: 9,
      geography_col: 'POINT(5 5)',
    };
    rows.push(row);

    // Row 10
    row = {
      row_num: 10,
      numeric_col: 123456,
      bignumeric_col: '99999999999999999999999999999.999999999',
    };
    rows.push(row);

    // Row 11
    row = {
      row_num: 11,
      time_col: '18:00:00',
    };
    rows.push(row);

    // Row 12
    row = {
      row_num: 12,
      timestamp_col: new Date('2022-01-09T03:49:46.564Z'),
    };
    rows.push(row);

    // Offset must equal the number of rows that were previously sent.
    offsetValue = 6;

    // Send batch.
    pw = writer.appendRows(rows, offsetValue);
    pendingWrites.push(pw);

    rows = [];

    // Row 13
    row = {
      row_num: 13,
      int64_list: [1999, 2001],
    };
    rows.push(row);

    // Row 14
    row = {
      row_num: 14,
      struct_col: {
        sub_int_col: 99,
      },
    };
    rows.push(row);

    // Row 15
    row = {
      row_num: 15,
      struct_list: [{sub_int_col: 100}, {sub_int_col: 101}],
    };
    rows.push(row);

    offsetValue = 12;

    // Send batch.
    pw = writer.appendRows(rows, offsetValue);
    pendingWrites.push(pw);

    const results = await Promise.all(
      pendingWrites.map(pw => pw.getResult())
    );
    console.log('Write results:', results);

    const {rowCount} = await connection.finalize();
    console.log(`Row count: ${rowCount}`);

    const response = await writeClient.batchCommitWriteStream({
      parent: destinationTable,
      writeStreams: [streamId],
    });

    console.log(response);
  } catch (err) {
    console.log(err.message, err);
  } finally {
    writeClient.close();
  }
}

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